Inspiration

Buyers lose deals because they can't visualize potential. A dated kitchen kills a sale — even when the bones are perfect. We wanted to close that gap between "what is" and "what could be."

## What it does
Paste any Zillow or Redfin URL. RoomLens scrapes the listing, analyzes the property, and generates AI-tailored renovation concepts specific to the neighborhood and price point. World
Labs then builds each concept into a navigable 3D world — so buyers can walk through a renovated version of a home before making an offer.

## How we built it

  • Firecrawl to scrape listing photos, price, and property details from Zillow/Redfin
  • Claude (Anthropic) to generate neighborhood-specific renovation styles and rich 3D world prompts
  • World Labs Marble API to generate navigable 3D environments from those prompts
  • Tavus for an AI avatar agent that narrates the renovated space
  • Supabase for session persistence and shareable world links
  • Next.js + Tailwind for the frontend

## Challenges we ran into
World Labs world generation is asynchronous and takes ~5 minutes — we had to build a polling system that survives Next.js API timeouts. We also hit API credit issues mid-hackathon and
had to debug undocumented request formats in real time.

## Accomplishments that we're proud of
We built a full end-to-end pipeline — from a raw Zillow URL to an AI-designed, 3D-generated renovated home — in one evening. The Claude-generated renovation briefs are genuinely tailored to each property's neighborhood and price point, not generic.

## What we learned
Async world generation requires careful UX — users need feedback at every stage or they'll think it's broken. We also learned that real estate data is messier than expected; Firecrawl's extraction handled it better than we anticipated.

## What's next for RoomLens
Listing agent integrations, multi-room apartment walkthroughs, and a shareable link product so agents can send buyers a personalized renovated tour of every listing they visit.

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